Research output per year
Research output per year
Personal profile
Research interests
Dr Thomas Day is a Clinical Research Fellow working as part of the Intelligent Fetal Imaging and Diagnosis (iFIND) project. He is a Paediatric and Fetal Cardiologist, and undertakes clinical work at The Evelina London Children's Hospital, part of Guy's and St Thomas' NHS Foundation Trust. His research interest is the use of artificial intelligence to improve screening for congenital heart disease.
Education/Academic qualification
Medicine, Master of Research, MRes (intercalated), University of Manchester
2006 → 2008
Award Date: 1 Jun 2008
Medicine, Bachelor of Medicine, MBChB, University of Manchester
2002 → 2008
Award Date: 1 Jun 2008
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Collaborations and top research areas from the last five years
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Outcome and Impact of Associated Left-Sided Cardiac Lesions in Coarctation of the Aorta Diagnosed During Fetal Life
Polyviou, S., Charakida, M., Miller, O. I., RSCN, T. W., Vigneswaran, T. V., Zidere, V., Day, T. G., Lloyd, D. F. A., Sharland, G. K. & Simpson, J. M., 1 Mar 2022, In: American Journal of Cardiology. 166, p. 114-121 8 p.Research output: Contribution to journal › Article › peer-review
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Artificial intelligence, fetal echocardiography, and congenital heart disease
Day, T. G., Kainz, B., Hajnal, J., Razavi, R. & Simpson, J. M., May 2021, In: Prenatal Diagnosis. 41, 6, p. 733-742 10 p.Research output: Contribution to journal › Review article › peer-review
13 Citations (Scopus) -
Detecting Outliers with Poisson Image Interpolation
Tan, J., Hou, B., Day, T., Simpson, J., Rueckert, D. & Kainz, B., 2021, Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 - 24th International Conference, Proceedings. de Bruijne, M., Cattin, P. C., Cotin, S., Padoy, N., Speidel, S., Zheng, Y. & Essert, C. (eds.). Springer Science and Business Media Deutschland GmbH, p. 581-591 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12905 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
13 Citations (Scopus) -
Learning normal appearance for fetal anomaly screening: Application to the unsupervised detection of Hypoplastic Left Heart Syndrome
Chotzoglou, E., Day, T., Tan, J., Matthew, J., Lloyd, D., Razavi, R., Simpson, J. & Kainz, B., 15 Nov 2020.Research output: Working paper/Preprint › Preprint
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Projects
- 1 Active
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Artificial intelligence to improve antenatal detection of congenital heart disease
NIHR National Institute For Health & Care Research
1/04/2021 → 31/03/2024
Project: Research